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Analysis and Allocation of Cancer-Related Genes Using Vague DNA Sequence Data

To test the equality of several independent multinomial distributions, the chi-square test for count data is applied. The existing test can be applied when complete information about the data is available. The complex process, such as DNA count, the existing test under classical statistics may misle...

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Detalles Bibliográficos
Autores principales: Aslam, Muhammad, Albassam, Mohammed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061958/
https://www.ncbi.nlm.nih.gov/pubmed/35518359
http://dx.doi.org/10.3389/fgene.2022.858005
Descripción
Sumario:To test the equality of several independent multinomial distributions, the chi-square test for count data is applied. The existing test can be applied when complete information about the data is available. The complex process, such as DNA count, the existing test under classical statistics may mislead. To overcome the issue, the modification of the chi-square test for multinomial distribution under neutrosophic statistics is presented in this paper. The modified form of the chi-square test statistic under indeterminacy/uncertainty is presented and applied using the DNA count data. From the DNA count data analysis, simulation, and comparative studies, the proposed test is found to be informative, springy, and good as compared with the existing tests.